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Wei Deng
Wei Deng
Researcher at Morgan Stanley
Zweryfikowany adres z purdue.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving
W Deng, J Pan, T Zhou, D Kong, A Flores, G Lin
The 14th International Conference on Web Search and Data Mining (WSDM'21), 2021
722021
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
W Deng, X Zhang, F Liang, G Lin
Advances in Neural Information Processing Systems (NeurIPS'19), 5563-5573, 2019
492019
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
W Deng, Q Feng, L Gao, F Liang, G Lin
The 37th International Conference on Machine Learning (ICML'20), 2020
392020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
W Deng, G Lin, F Liang
Advances in Neural Information Processing Systems (NeurIPS'20), 2020
262020
Information Directed Sampling for Sparse Linear Bandits
B Hao, T Lattimore, W Deng
Advances in Neural Information Processing Systems (NeurIPS'21), 2021
162021
On Convergence of Federated Averaging Langevin Dynamics
W Deng, Q Zhang, YA Ma, Z Song, G Lin
http://arxiv.org/abs/2112.05120, 2022
152022
An Adaptively Weighted Stochastic Gradient MCMC Algorithm for Monte Carlo simulation and Global Optimization
W Deng, G Lin, F Liang
Statistics and Computing 32 (58), 1-24, 2022
122022
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
W Deng, Y Chen, S Fang, F Li, NT Yang, Y Zhang, K Rasul, S Zhe, ...
The 40th International Conference on Machine Learning (ICML'23), 2023
112023
Bayesian Sparse Learning with Preconditioned Stochastic Gradient MCMC and its Applications
Y Wang, W Deng, G Lin
Journal of Computational Physics, 2021
112021
Interacting Contour Stochastic Gradient Langevin Dynamics
W Deng, S Liang, B Hao, G Lin, F Liang
The 10th International Conference on Learning Representations (ICLR'22), 2022
92022
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications
R Zhang, W Deng, MY Zhu
The 9th Asian Conference on Machine Learning (ACML'17), 2017
72017
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
W Deng, Q Feng, G Karagiannis, G Lin, F Liang
The 9th International Conference on Learning Representations (ICLR'21), 2021
62021
An Adaptive Hessian Approximated Stochastic Gradient MCMC Method
Y Wang, W Deng, G Lin
Journal of Computational Physics, 110150, 2021
52021
Batch Normalization Preconditioning for Stochastic Gradient Langevin Dynamics
S Lange, W Deng, Q Ye, G Lin
Journal of Machine Learning, 2023
22023
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
H Zheng, W Deng, C Moya, G Lin
International Conference on Artificial Intelligence and Statistics (AISTATS'24), 2024
12024
On Convergence of Approximate Schrödinger Bridge with Bounded Cost
W Deng, Y Chen, NT Yang, H Du, Q Feng, RTQ Chen
Learning, Control, and Dynamical Systems Workshop (ICML'23 Workshop), 2023
12023
Non-reversible Parallel Tempering for Deep Posterior Approximation
W Deng, Q Zhang, Q Feng, F Liang, G Lin
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI'23), 2023
12023
Reflected Schrödinger Bridge for Constrained Generative Modeling
W Deng, Y Chen, NT Yang, H Du, Q Feng, RTQ Chen
https://arxiv.org/abs/2401.03228, 2024
2024
Non-convex Bayesian Learning via Stochastic Gradient Markov Chain Monte Carlo
W Deng
Purdue University, 2021
2021
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